| 1. |
- Klionsky, Daniel J., et al.
(författare)
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Guidelines for the use and interpretation of assays for monitoring autophagy in higher eukaryotes
- 2008
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Ingår i: Autophagy. - : Landes Bioscience. - 1554-8627 .- 1554-8635. ; 4:2, s. 151-175
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Forskningsöversikt (refereegranskat)abstract
- Research in autophagy continues to accelerate,1 and as a result many new scientists are entering the field. Accordingly, it is important to establish a standard set of criteria for monitoring macroautophagy in different organisms. Recent reviews have described the range of assays that have been used for this purpose.2,3 There are many useful and convenient methods that can be used to monitor macroautophagy in yeast, but relatively few in other model systems, and there is much confusion regarding acceptable methods to measure macroautophagy in higher eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers of autophagosomes versus those that measure flux through the autophagy pathway; thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from fully functional autophagy that includes delivery to, and degradation within, lysosomes (in most higher eukaryotes) or the vacuole (in plants and fungi). Here, we present a set of guidelines for the selection and interpretation of the methods that can be used by investigators who are attempting to examine macroautophagy and related processes, as well as by reviewers who need to provide realistic and reasonable critiques of papers that investigate these processes. This set of guidelines is not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to verify an autophagic response.
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| 2. |
- Caro, J. J., et al.
(författare)
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Economic implications of extended-release metoprolol succinate for heart failure in the MERIT-HF trial: a US perspective of the MERIT-HF trial
- 2005
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Ingår i: J Card Fail. - 1071-9164. ; 11:9, s. 647-56
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The MERIT-HF trial demonstrated improved survival and fewer hospitalizations for worsening heart failure with extended-release (ER) metoprolol succinate in patients with heart failure. This study sought to estimate the economic implications of this trial from a US perspective. METHODS AND RESULTS: A discrete event simulation was developed to examine the course of patients with heart failure. Characteristics of the population modeled, probabilities of hospitalization and death with standard therapy, and risk reductions with ER metoprolol succinate were obtained from Metoprolol CR/XL Randomized Intervention Trial in Chronic Heart Failure (MERIT-HF) and evaluated in weekly cycles. Direct medical costs were estimated from US databases in 2001 US dollars. Uncertainty in inputs was incorporated and analyses were carried out to estimate events prevented total and net costs. The model predicts that ER metoprolol succinate will prevent approximately 7 deaths and 15 hospitalizations from heart failure per 100 patients over 2 years. Compared with standard therapy alone, this translates to a cost reduction between $395 and $1112 per patient, depending on whether the costs of hospitalizations for other causes are included. Savings were maintained in 90% of the simulations. CONCLUSION: This analysis predicts that the positive effect of ER metoprolol succinate on mortality and morbidity demonstrated in MERIT-HF leads to substantial savings.
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| 3. |
- Gottlieb, C., et al.
(författare)
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Feasibility study on transient identification in nuclear power plants using support vector machines
- 2006
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Ingår i: Nuclear Technology. - 0029-5450 .- 1943-7471. ; 155:1, s. 67-77
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Tidskriftsartikel (refereegranskat)abstract
- Support vector machines (SVMs), a relatively new paradigm in statistical learning theory, are studied for their potential to recognize transient behavior of detector signals corresponding to various accident events at nuclear power plants (NPPs). Transient classification is a major task for any computer-aided system for recognition of various malfunctions. The ability to identify the state of operation or events occurring at an NPP is crucial so that personnel can select adequate response actions. The Modular Accident Analysis Program, version 4 (MAAP4) is a program that can be used to model various normal and abnormal events in an NPP. This study uses MAAP signals describing various loss-of-coolant accidents in boiling water reactors. The simulated sensor readings corresponding to these events have been used to train and test SVM classifiers. SVM calculations have demonstrated that they can produce classifiers with good generalization ability for our data. This in, turn indicates that SVMs show promise as classifiers for the learning problem of identifying transients.
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